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ML Data QA Lead, MLO

Apple· Software and Services / Intelligent System Experience (ISE) / Machine Learning Data Ops Team
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Cupertino, California$120.9k - $249kFull-timePosted 2mo ago

About the role

Lead data quality assurance for ML features by defining quality standards, building QA tooling, and coordinating with Data Program Managers, Data Engineers, and R&D partners to ensure high-quality ML datasets for model training across Apple devices.

Responsibilities

  • Owns the quality strategy and roadmap across the data request life cycle, defining the workflows and process controls that anticipate failure modes, expose edge cases, detect anomalies, and surface issues early rather than at delivery.
  • Translates ambiguous quality expectations into explicit, documented standards and decision rules that vendors, reviewers, and partner teams can apply consistently.
  • Runs quality assurance and quality control checks across pilot and production phases, and validates trends before datasets reach R&D.
  • Designs and builds new QA tools, and extends the review interfaces, data pipelines, and reporting the team already relies on, using AI-assisted development.
  • Introduces model-assisted checks into review workflows, iterating on prompts and measuring agreement against human labels before those checks are relied on.
  • Verifies analyses, metrics, and generated artifacts independently before they are published.
  • Leads internal and external quality analysts, and presents quality findings, statistics, and recommendations to project teams, partner organizations, and vendors.
  • Partners with Collection, Annotation, and R&D teams to pin down project specifications, reduce subjectivity, and ensure guidelines are unambiguous to everyone who applies them.

Qualifications

  • Bachelor's degree, or equivalent practical experience.
  • 4+ years of experience in ML data operations, data quality, or a comparable data-centric quality function.
  • Working proficiency in Python for data manipulation and reporting.
  • Hands-on experience using AI coding assistants to build working QA tools or analysis.
  • Strong written and verbal communication skills.
  • Experience designing labeling taxonomies or annotation guidelines and adjudicating ambiguous cases with vendors.
  • Experience leading internal or external quality analysts and designing or running human rating and evaluation programs, including rater calibration, gold sets, and ongoing quality monitoring.
  • Familiarity with statistical quality methods, including sampling strategy, inter-rater agreement, acceptance rates, and error magnitude and confidence analysis.
  • Experience designing and iterating on prompts for quality checks assisted by large language models (LLMs) or vision language models (VLMs).
  • Experience building internal QA tooling end to end, such as a review interface, a data pipeline, or a browser-based dashboard (HTML, CSS, JavaScript).
  • Excellent attention to detail with a passion for problem solving, investigation, and root cause analysis.
  • Strong critical thinking, with the judgment to question assumptions and validate a quality signal before relying on it.
  • Excellent project management, analytical, and organizational skills, with the ability to manage several projects in parallel in a dynamic environment with shifting priorities.

Skills

Required:Python for data manipulation and reportingAI-assisted tooling for QAQuality strategy and governanceLeadership of QA teams
Nice to have:Statistical quality methodsPrompt design for QA with LLMs/VLMsQA tooling development (UI/data pipelines)

Benefits

  • Comprehensive medical and dental coverage
  • retirement benefits
  • discounted products and free services
  • education reimbursement for advancing career (tuition)
  • potential discretionary bonuses or commission payments
  • relocation
Last updated Oct 23, 2026. Interested? Apply on the company site.

About Apple

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